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Apr 1, 2012 (Vol. 32, No. 7)

Appreciating the Art of Assay Development

  • Two for the Price of One

    But sometimes a new assay is literally just two established techniques wrapped up together.

    Due to the high cost associated with high-throughput screening, “people usually do not run two assay platforms for the same target with the same library,” said Yuhong Du, Ph.D., associate director of the Chemical Biology Discovery Center at Emory University. “You have to select one.”

    Both fluorescence polarization (FP) and time resolved fluorescence resonance energy transfer (TR-FRET) techniques have been widely used in high-throughput screening for many years. Each has its drawbacks, each generates hit lists that tend to only partially overlap, and each acquires it own set of data: FP measures the rotation of the molecule (which is slowed by interaction with another molecule), while FRET measures the proximity of the FRET donor and acceptor molecules. Many benchtop multilabel readers can read both.

    Because the two assays do not interfere with one another, Dr. Du and her colleagues decided to combine them together “in one well at the same time, to monitor the same interaction, to give us an information-rich primary HT screening,” she explained. “You don’t need to run two assays in parallel, instead you run two assay platforms in the same well.”

    Of course, if it was just a matter of taking two readings, someone would have come up with the Dual-Readout F2 assay a long time ago. To satisfy the requirements for both, components in the reaction require tedious optimization, generally involving bidirectional titrations of two binding partners. And sometimes compromise: for example, more protein may be needed to boost the signal for one readout, yet it saturates that of the other.

    As a model study, F2 was used to screen a library of 100,000 compounds that disrupt the interaction between the Mcl-1 anti-apoptosis protein and its known inhibitor peptide Noxa.

    By taking only the compounds that were positive in both assays, they were able to efficiently prioritize their hits based on behaviors of positive compounds in these two platforms for a follow-up study. And, Dr. Du pointed out, simply repeating the same screening with a single readout would not add significant information to the hit list, as was achieved in a single step with the F2 assay.

  • Enzymology Is a Competitive Business

    Click Image To Enlarge +
    Scientists in Sanford-Burnham’s Conrad Prebys Center for Chemical Genomics use industrial-scale high-throughput workstations to screen chemical libraries against biological targets.

    When Eduard Sergienko, Ph.D., was looking to set up appropriate assays to identify modulators of tissue-nonspecific alkaline phosphate (TNAP), he realized that buffers such as diethanolamine (DEA), traditionally used in alkaline phosphatase (AP) assays, can actually participate as a substrate in the reaction, re-directing it toward transphosphorylation.

    This could pose a problem since a high concentration of DEA routinely employed for boosting the assay sensitivity would saturate the reaction, making it nearly impossible to find competitive inhibitors.

    “The physiological significance of the transphosphorylation reaction and the identity of its alcohol substrate are still unknown,” the director of assay development at Conrad Prebys Center for Chemical Genomics (CPCCG) at Sanford-Burnham Medical Research Institute said. “We wanted to find compounds that would inhibit different potential enzyme activities and thus wanted to have compounds with various mechanisms of action.”

    Dr. Sergienko and his colleagues adapted CDP-star, a chemiluminescence substrate widely used for detection of AP in blotting, allowing them to eliminate DEA if they so chose. The assay was sensitive enough, and with a large enough dynamic range, to screen at low enzyme concentration and with the substrate at Km. “One can emphasize a certain mechanism of action by playing with the concentration of substrate relative to the Km level,” he explained.

    They screened TNAP against the Molecular Library Screening Center Network (MLSCN) collection containing 64,394 compounds and found three major categories of inhibitor structural scaffolds along with some minor categories and singletons. One of these scaffolds contained the first competitive inhibitors for TNAP, and for APs in general.

    Only four of the 55 hits identified by the high-throughput luminescent assay screen could be confirmed in a colorimetric assay performed with high DEA concentration—giving evidence that it is perhaps directly competing for the enzyme’s binding site.

    To support TNAP lead-optimization efforts at CPCCG, Dr. Sergienko and his team have gone on to develop a biomarker assay for AP activity within blood plasma that can be run at physiological pH using small-volume aliquots of minimally diluted plasma samples—making it amenable to high-throughput methodology.

    This approach allowed testing of structure-activity relationship compounds and predicting their efficacy in vivo. In addition, the biomarker assay allows monitoring activity of TNAP in the samples taken from animals after dosing them with TNAP inhibitors in pharmacokinetic studies, providing pharmacodynamic information for animal models relevant to TNAP.

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